存在RF干扰时基于RSS的无人机检测
RSS-Based Detection of Drones in the Presence of RF Interferers
摘要：
无人机将在各种商业、政府和军事部门有广泛的应用，从消费品的交付到搜索和救援行动。为了维护人员和基础设施的安全，快速准确地检测不合作的无人机变得至关重要。在本文中，我们制定了一个接收信号强度（RSS）为基础的检测器，利用现有的无线基础设施，可能已经服务于其他设备。因此，检测器可以在混合视线（LOS）和非LOS（NLOS）环境中检测隐藏在射频（RF）干扰和热噪声中的无人机信号的存在。我们开发了虚警概率和无人机检测概率的解析表达式，该表达式量化了聚合干扰和空对地（A2G）传播特性对单个传感器检测性能的影响。我们还提供了平均网络检测概率的解析表达式，它捕获了传感器密度对网络检测覆盖率的影响。最后，我们找到的临界传感器密度，最大化的平均网络检测概率为一个给定的要求的虚警概率。
英文摘要：
Drones will have extensive use cases across various commercial, government, and military sectors, ranging from delivery of consumer goods to search and rescue operations. To maintain the safety and security of people and infrastructure, it becomes critically important to quickly and accurately detect non-cooperating drones. In this paper we formulate a received signal strength (RSS) based detector, leveraging the existing wireless infrastructures that might already be serving other devices. Thus the detector can detect the presence of a drone signal buried in radio frequency (RF) interference and thermal noise, in a mixed line-of-sight (LOS) and non-LOS (NLOS) environment. We develop analytical expressions for the probability of false alarm and the probability of detection of a drone, which quantify the impact of aggregate interference and air-to-ground (A2G) propagation characteristics on the detection performance of individual sensors. We also provide analytical expressions for the average network probability of detection, which capture the impact of sensor density on a network's detection coverage. Finally, we find the critical sensor density that maximizes the average network probability of detection for a given requirement of the probability of false alarm.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
